Deep learning vs. machine learning

Understanding deep learning vs machine learning can help you keep up with the latest AI advances. Learn more about these two essential AI topics.

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By: Thomas Broderick, Edited by: Gabriela Pérez Jordán, Reviewed by: Jeff Le

Last updated: June 25, 2025

As of April 2025, self-driving taxis shuttle passengers across four major American cities. This technology, seemingly impossible until just a few years ago, would not exist without deep learning, a branch of machine learning.

Deep learning and machine learning are revolutionizing not just how people move but also how they work, shop, learn, and live.

Understanding deep learning vs. machine learning begins with knowing that both are important areas of AI research. Machine learning also acts as the foundation upon which AI researchers make deep learning breakthroughs.

Nested proportional area chart displaying deep learning in the innermost circle, followed by machine learning, and finally AI. The chart shows that deep learning is a subset of machine learning, and machine learning is a subset of the field of AI.

Artificial intelligence: Artificial intelligence is a subfield of computer science that aims to build computer systems that can act, reason, and learn like humans.

Machine learning: Machine learning uses mathematical algorithms to teach computers how to recognize patterns and make predictions.

Deep learning: Deep learning builds upon machine learning by providing AI systems with artificial neural networks. These networks and large datasets let machine learning AI produce original content.

What is machine learning?

AI researchers who work in machine learning teach computers to learn and act independently. Mathematical algorithms and training help AI systems recognize patterns in large datasets. Researchers then expose machine learning AI to new data to see if it can make accurate predictions.

You likely benefit from machine learning's predictive capabilities every day. Common uses include:

Streaming services that recommend new movies
Virtual assistants that answer your questions
Email services that filter out spam
Programs that translate text into a foreign language

What is deep learning?

A branch of machine learning, deep learning uses artificial neural networks resembling the biological ones in the human brain. This design approach lets deep learning AI perform tasks that machine learning AI cannot, such as:

Driving a car autonomously
Translating natural speech into a foreign language
Writing computer code

Deep learning also makes generative AI possible. This technology can not only recognize patterns but also create original works based on those patterns. Following a simple prompt, generative AI can produce a poem or story in the style of a well-known author or generate an image or visual.

Key differences

Machine learning

Can function autonomously in some applications
Uses mathematical algorithms and artificial neural networks to function
Can make new information by analyzing large amounts of preexisting information
Can interact with people through natural speech

Deep learning

Requires human input to function
Uses mathematical algorithms to function
Can make suggestions from preexisting information
Can interact with people through text-based input

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Frequently asked questions about deep learning and machine learning

How is deep learning different from AI?

Deep learning is a branch of AI in which AI systems learn much like humans. This process involves large language models (LLMs) and artificial neural networks. LLMs analyze large amounts of print and visual data, draw conclusions based on pattern recognition, and create new content based on minimal user input.

Should I learn deep learning or machine learning first?

Consider beginning your education with machine learning, as it is the academic foundation for deep learning. The AI fundamentals you learn in machine learning courses will prepare you to tackle the latest deep learning advances. Explore edX AI certificates to get started.

Is ChatGPT a deep learning model?

Yes, the LLMs that power ChatGPT can create original responses to user queries. Deep learning also lets ChatGPT write more lengthy, detailed, and accurate responses than earlier machine learning models could achieve. Other deep learning models include Gemini, Claude, and Perplexity.